The research on meta-job scheduling heuristics in heterogeneous environments
- Jilin University, Changchun (China). College of Computer Science and Technology; The People’s Liberation Army, Huludao (China)
- Jilin University, Changchun (China). Department of Environmental Science and Key Laboratory of Groundwater Resources and Environment, Ministry of Education
- Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
As the core of rational utilization of computing resources, the scheduling algorithm has gained the interest of many researchers. Aimed at meta-job scheduling in heterogeneous environments, this paper puts forward three algorithms: the meta-job scheduling algorithm based on deviation (MaxD-min heuristic), the meta-job scheduling algorithm based on relative deviation (MaxRD-min heuristic), and the Cordwood algorithm (CA). The former two Algorithm are improvements of the classic Min-min algorithm. The latter CA algorithm is a new method that tries to place each building block on the tray with minimal amount of Sufferage. In conclusion, the result of experimenting shows that the three algorithms, in comparison to Min-Min and Max-Min algorithm, can effectively reduce the total span of scheduling (makespan).
- Research Organization:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
- Sponsoring Organization:
- USDOE
- Grant/Contract Number:
- AC05-00OR22725
- OSTI ID:
- 1468073
- Journal Information:
- Journal of Intelligent & Fuzzy Systems, Vol. 34, Issue 2; ISSN 1064-1246
- Publisher:
- IOS PressCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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